{"id":"W2085318923","doi":"10.1117/1.jei.21.1.013016","title":"Non-local pairwise energy-based model for the high-dynamic-range image compression problem","year":2012,"lang":"en","type":"article","venue":"Journal of Electronic Imaging","topic":"Image Enhancement Techniques","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"","keywords":"Tone mapping; Computer science; Pairwise comparison; Range (aeronautics); Gradient descent; Pixel; High dynamic range; Representation (politics); Image compression; Image (mathematics); Artificial intelligence; Algorithm; Energy (signal processing); Computer vision; Dynamic range; Mathematics; Image processing; Artificial neural network","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004802812,0.0007277275,0.0006881776,0.0004351485,0.0002472352,0.0006752882,0.001703961,0.001257761,0.002653372],"category_scores_gemma":[0.001117592,0.0002736507,0.0006161401,0.0004457006,0.000730972,0.001383763,0.0008800413,0.00127009,0.0004218823],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000540252,"about_ca_system_score_gemma":0.0004823175,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001229732,"about_ca_topic_score_gemma":0.001187303,"domain_scores_codex":[0.9997724,0.00006877903,0.000007026046,0.00004466944,0.00008622184,0.00002096396],"domain_scores_gemma":[0.9997074,0.000160242,0.0000431201,0.0000281918,0.00003713221,0.00002384839],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003066923,0.00004745959,0.0001794533,0.00007369166,0.00002594465,0.0001485886,0.00004622426,0.8997657,0.005312476,0.07733616,0.0009475572,0.0160861],"study_design_scores_gemma":[0.000002534755,0.00001066778,0.0000336502,0.000001535256,0.000002390684,0.00002618509,0.000002780877,0.9931102,0.0002910779,0.006327545,0.0001880202,0.000003413147],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01337907,0.0002150938,0.9835352,0.0002596756,0.00002276342,0.00002294235,0.00003288422,0.00004649542,0.002485846],"genre_scores_gemma":[0.7905293,0.001185676,0.1827893,0.0002838514,0.0001270526,0.0003654062,0.0002212592,0.0001724203,0.02432578],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002653372,"threshold_uncertainty_score":0.008876383,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006310101333078258,"score_gpt":0.2494770660464735,"score_spread":0.2431669647133953,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}